- Alessandro Saffiotti.
Autonomous Robot Navigation: a fuzzy logic approach.
- PhD Thesis. Faculté de Sciences Appliquées,
Université Libre de Bruxelles, Belgium. October 1998.
The focus of this thesis is on autonomous robot
navigation in real-world, unstructured environments. By this we mean
the ability to move purposefully and without human intervention in
environments that have not been specifically engineered for the robot.
It is generally recognized that three of the major sources of difficulty
in this task are: (1) the pervasive presence of uncertainty, e.g., in
sensing and prior information; (2) the need to coordinate activities
aimed at different goals, e.g., moving to a given location while
avoiding unexpected obstacles; and (3) the need to integrate processes
at different levels of abstractions, e.g., strategic planning and
Fuzzy logic, a mathematical formalism based on the theory of fuzzy sets,
provides tools that are of potential interest here. First, fuzzy logic
is the basis of fuzzy control, which is used in an increasing number of
applications characterized by large uncertainty. Second, fuzzy logic
offers a wide range of aggregation operators, that can be used to trade
off different goals. Finally, the intrinsic ability of fuzzy logic to
integrate numerical ("fuzzy") and symbolic ("logic") computation
suggests its use as a formalism to integrate numeric control and
symbolic planning. While many applications of fuzzy control have
appeared in the autonomous robotics literature, these other uses of
fuzzy logic have received little attention to this date.
This thesis explores some possible uses of fuzzy logic for autonomous
robot navigation. To do so, we develop and validate solutions based on
fuzzy logic to some instances of the three problems above; we do so in a
behavior-based framework. This thesis makes the following
- A practical solution to the problem of the heuristic design and
implementation of simple navigation behaviors, based on the
techniques of fuzzy control;
- A new solution to the problem of behavior coordination,
based on the use of fuzzy arbitration rules and fuzzy aggregation
- A formal analysis of the link between the composition of behaviors
and the satisfaction of (complex) goals, based on fuzzy logic;
- A new solution to the problem of the integration of
high-level task planning and low-level motion control, based on the
automatic generation of complex combined behaviors, called B-plans.
The research methodology followed ties formal analysis and practical
testing. All the techniques presented have been extensively validated
in experiments run on real robots.
|Designed and maintained by
Last updated: Apr 27, 2007